RESEARCH Open Access
The impact of savings on economic growthin a developing country (the case ofKosovo)Artur Ribaj1* and Fitim Mexhuani2
* Correspondence: [email protected] of Economics, University ofTirana, Tirana, AlbaniaFull list of author information isavailable at the end of the article
Abstract
The correlation between savings and economic growth has been the subject ofresearch for some well-known economists. This study provides further insight onsuch correlation by examining the case of Kosovo from both a qualitative andquantitative research methodology. The data used was from 2010 to 2017 and hasbeen analyzed using the augmented Dickey-Fuller tests, Johansen cointegrationtests, and Ganger causality test. The test of the unit root confirms stationarity, andthe regression results showed that deposits have a significant positive impact onKosovo’s economic growth, because savings stimulate investment, production, andemployment and consequently generate greater sustainable economic growth.Furthermore, loans and remittances also help boost the economy of Kosovo throughtheir direct impact on investment. This paper confirms that countries whose nationalsavings rate is high are not dependent on foreign direct investment; consequently,the risk arising from volatile foreign direct investment decreases significantly.
Keywords: Behavioral finance, Central banks and their policies, Corporate financeand governance, Financial institutions and services, Multiple or simultaneousequation models
JEL Classification: G4, E58, G3, G2, C3
BackgroundFor the past 17 years, Kosovo has been experiencing major economic transformation,
resulting in a significant economic growth. Although Kosovo has the highest economic
growth compared to any other country in Southeast Europe, in the last 5 years, growth
has decelerated fluctuating at an average pace of 3.8 to 4.4% as per CEIC data1. Accu-
mulation of financial capital has been highlighted as the main factor regulating devel-
opment to some degree—and since savings have increased in Kosovo, the situation
begs the question of how an increase in savings contributes to the overall economic
growth of a developing country like Kosovo.
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1https://www.ceicdata.com/en/indicator/kosovo/real-gdp-growth
Journal of Innovation andEntrepreneurship
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 https://doi.org/10.1186/s13731-020-00140-6
Countries with higher rates of savings have had a faster economic growth than those
with lower saving rates. Capital accumulation creates greater opportunities for produc-
tion and the productivity of a country by providing an additional income stream for
countries like Kosovo. In that regard, the United Nations Conference on Trade and De-
velopment “Development and Globalization: Facts and Figures”2 (2004) emphasizes that
the main factor in increasing in-country capital is the increase of savings and that, in
that regard, developing countries should prioritize programs that promote domestic
savings, in order for capital to be invested towards the most productive practices. This
paper based on literature review and empirical results confirm the impact of savings for
sustainable economic growth of Kosovo and recommends politicians to implement pol-
icies that encourage gathering of savings in Kosovo banks from all citizens of Kosovo
wherever they are.
MethodsTo effectively implement the Johansen cointegration test and to find out the relation-
ship between the gross domestic product (GDP) and domestic savings, this study ana-
lyzed the annual data of 10 commercial banks3 in Kosovo for the period of 2010–2017.
The methods used for the analysis were the Dickey-Fuller (DF), augmented Dickey-
Fuller (ADF), and the Ganger causality tests. The cointegration will inform us about the
relationship in the short and long terms among the two variables, while on the other
hand, causality indicates that (1) either X is causing Y, (2) either Y is causing X, or (3)
both variables have a causal relationship with each other. Initially, the time series
should be tested for stationarity through the ADF test and Philip Perron, usually the
lower scale test and Granger. On the other hand, the augmented Dickey-Fuller test
(ADF test) is a common statistical test used to test whether a given time series is sta-
tionary or not (Machine Learning Plus, 2019). If the series are non-stationary, then they
should be included in the model in their stationary form and then proceed with analyz-
ing the linear regression model. The equation is expressed in the form of: Yt = μ + p ×
Yt−1 + ɛt. The Ganger causality test denotes that any change of factor X to an earlier
time period (t-k) affects the Y variable at time t. Therefore, the hypothesis is H0: X does
not cause (Granger cause) with Y in the first regression; the growth of savings in the
commercial banks of Kosovo positively affects sustainable growth in Kosovo.
ResultsThe methods used for the analysis of this study fit time series and mainly the Ganger
causality, Dickey-Fuller (DF), and augmented Dickey-Fuller (ADF) tests. Initially, the
time series are tested for stationarity through the ADF test. If the series is non-
stationary, then they are included in the model in their stationary form and then ana-
lyzed through the linear regression model. The equation is as follows: Yt = μ + p × Yt−1
+ ɛt.We point out stationarity through Fig. 1 that refers to the GDP values for the period
of 2010–2017. It is worth noting that if the series tends to increase or descend in time,
then it can be said that the stationary condition may have been compromised.
2https://unctad.org/en/Docs/gdscsir20041_en.pdf3Kosovo has licensed 11 banks. Ten of them are doing banking in the all cities of Kosovo. One of them isdoing business only in north of Mitrovica, and it has less than 1% of Kosovo deposits.
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 2 of 13
Otherwise, it can be a series of unit roots. Statistical data shows that GDP (nominal
rate) has an upward trend from 2010 to 2017. Hence, the series of GDP values is a
series of root units.
Applying the Ganger causality test
Before developing the appropriate model, we refer to the analysis of the Ganger causal-
ity test to analyze the role of each variable in the model in order to properly identify
which one is the cause and which is the consequence. The data in Table 1 shows that
none of the variables causes the “no Granger cause” between them. Hence, this allows
for building a linear equation where GDP is the dependent variable, while deposits, re-
mittances, and loans are independent variables.4
Upon successfully passing this test, we can continue conducting the following tests.
Application of augmented Dickey-Fuller test
We further analyze our series by referring to the augmented Dickey-Fuller (ADF) test
as Table 2.
According to its data, the value of t-statistics in the ADF test is:
t-statistics = 1.509 > −5.119 (1% level)
− 3.519 (5% level)
− 2.898 (10% level)
As the results indicate, we are dealing with a non-stationary series where the prob-
ability value is 0.9947.
Referring to EViews data regarding the first difference we observe that: t-statistics =
− 3.09 > − 5.11 (1% level), > − 3.51 (5% level), and < − 2.89 (10% level).
Probability F (statistics) = 0.03 entails that our series is stationary in its first
differences and is considered a series integrated into the first differences. The value of
R2 = 0.70 is a relatively high value. Since the value of F-statistic = 9.58 (Table 2), we
Fig. 1 GDP 2010–2017. Source: Data published by commercial banks and CBK processed by the authors
4Note: The following tables have been developed with the aid of EViews software, which is an “econometric,statistics, and forecasting package.” The software is widely available online and uses standardized tables andcharts. Therefore, many of technical terms in these tables are repetitive and will most likely appear exactlythe same in similar studies. For more information about the software used, refer to https://www.eviews.com/Discovering/whatiseviews.html.
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 3 of 13
can reject hypothesis H0 and include GDP in linear models. To reinforce this, Table 3
shows the data for the value of R2 and the corresponding value of F-statistic as follows:
Therefore, we can develop a linear equation where GDP is the dependent variable,
while deposits, remittances, and loans are independent variables. We tested this in the
Ganger causality test applied in the previous steps. Considering what we want to test,
and the previous test applications, we have built the following equations.
Applying linear regression equations
Equation with deposit as the only factor
Initially, we utilize a simple linear equation, considering only deposits as an
independent variable. Hence, the equation is as follows:
GDP ¼ 1:842422þ 0:001444 depositsð Þ:
Considering the fact that Prob. (F-statistic) = 0.000, and that the value of F-statistics
is also relatively high F-statistics = 330.8186, it appears that the model predicts 98.2%
change in the value of GDP, resulting from a change in the factor deposit (reflected in
Table 4). So, if the deposit factor increases by 1 unit, the value of GDP (nominal rate)
will increase by 0.001444 times. The coefficient in front of the “deposit” factor has a
positive value as expected. This means that deposits are an important factor in GDP
growth, thus addressing the first objective of this study. Demonstrating the relationship
between deposit accumulation/savings in Kosovo and Kosovo’s economic growth, please
refer to Table 4.
Equation with two factors (deposits and loans)
If the deposit factor increases the credit factor, further analyzing the effect of these
factors is referred to again as the construction of the loan. Thus, the data presented in
the table below shows that when deposits and loans are taken into account, GDP is
calculated as GDP = 1.771828 + 0.001121 (deposits) + 0.000459 (loans). The equation
Table 1 Ganger causality test
Pairwise Granger causality testsDate: August 17, 2018; Time: 09:48Sample: 2010–2017Lags: 2
Null hypothesis: Obs F-statistic Prob.
Deposits does not Granger cause GDP 6 952.073 0.0229
GDP does not Granger cause DEPOSITS 58.3679 0.0922
Credits does not Granger cause GDP 6 41.9991 0.1085
GDP does not Granger cause CREDITS 2.47142 0.4102
Remittances does not Granger cause GDP 6 0.71625 0.6412
GDP does not Granger cause remittances 1.65366 0.4818
Credits does not Granger cause deposits 6 6.64755 0.2645
Deposits does not Granger cause credits 5.40781 0.2909
Remittances does not Granger cause deposits 6 1.65669 0.4815
Deposits does not Granger cause remittances 2.83038 0.3875
Remittances does not Granger cause credits 6 5.05721 0.3000
Credits does not Granger cause remittances 3.98526 0.3339
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is statistically valid since the value of Prob. (F-statistic) = 0.0000 and the value of F-
statistic = 158.2999. The equation shows that the impact of deposits is higher
compared to that of loans as the deposits’ β coefficient is higher despite both
coefficients being positive and indicating that the growth of both factors affects the
overall GDP growth rate. Yet, the probability of the deposit factor is smaller by 0.0339,
confirming, once again, the importance of the deposits factor compared to other
factors. Demonstrating the relationship in the case of Kosovo in Table 5.
Equation with remittances as the only factor
When referring to the above equation, where remittances have a significant coefficient,
we formulate another equation deliberating the correlation between GDP and
remittances. As per the data in Table 7, the equation is as follows: GDP = 41.764384 +
0.01043 (remittances). The R2 = 10.1% is a relatively small percentage compared to the
other coefficients, which shows that remittances along cannot be a determining factor
in GDP growth; they support but do not determine. This is the reason why first
remittances, in interaction with other factors such as deposits or loans, have a
significant impact on GDP. This is also confirmed by the value of Prob. (F-statistic) =
0.442 and the (rather low) value of F-statistic = 0.675427. Demonstrating the
relationship in the case of Kosovo in Table 6.
Table 2 Augmented Dickey-Fuller test for GDP
Null hypothesis: GDP has a unit rootExogenous: ConstantLag length: 1 (automatic—based on SIC, maxlag = 1)
t-statistic Prob.*
Augmented Dickey-Fuller test statistic 1.509007 0.9947
Test critical values: 1% level − 5.119808
5% level − 3.519595
10% level − 2.898418
* McKinnon (1973) one-sided p valuesWarning: Probabilities and critical values calculated for 20 observations and may not be accurate for a samplesize of 6.Augmented Dickey-Fuller test equationDependent variable: D (GDP)Method: Least squaresDate: July 24, 2018; Time: 19:04Sample (adjusted): 2012–2017Included observations: 6 after adjustments
Variable Coefficient Std. error t-statistic Prob.
GDP (− 1) 0.190513 0.126251 1.509007 0.2284
D (GDP (− 1)) 0.951048 0.522726 1.819401 0.1664
C − 1.034414 0.819969 − 1.261529 0.2963
R2 0.534089 Mean-dependent var. 0.266667
Adjusted R2 0.223482 S.D.-dependent var. 0.061210
S.E. of regression 0.053938 Akaike info. criterion − 2.695095
Sum squared resid 0.008728 Schwarz criterion − 2.799215
Log likelihood 11.08528 Hannan-Quinn criterion − 3.111897
F-statistic 1.719502 Durbin-Watson stat. 1.898931
Prob. (F-statistic) 0.318020
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 5 of 13
Equation with deposits and remittances as factors
Adding the remittances factor to this model will produce the following results: GDP =
1.806295 + 0.001426 (deposits) + 0.000143 (remittances). This model, as well, has a
high definite value of R2 = 98.4%—here, among the two factors of this model, the
deposit factor is more important as the propensity is smaller Prob = 0.000.
Demonstrating the relationship in the case of Kosovo in Table 7.
Table 3 ADF test for the first difference
Null hypothesis: D(GDP) has a unit root.Exogenous: ConstantLag length: 0 (automatic—based on SIC, maxlag = 1)
t-statistic Prob.*
Augmented Dickey-Fuller test statistic − 3.096283 0.0797
Test critical values: 1% level − 5.119808
5% level − 3.519595
10% level − 2.898418
*McKinnon (1973) one-sided p valuesWarning: Probabilities and critical values calculated for 20 observations and may not be accurate for a sample size of 6Augmented Dickey-Fuller test equationDependent variable: D(GDP.2)Method: Least squaresDate: July 24, 2018; Time: 19:40Sample (adjusted): 2012–2017Included observations: 6 after adjustments
Variable Coefficient Std. error t-statistic Prob.
D (GDP (− 1)) − 0.767405 0.247847 − 3.096283 0.0364
C 0.198826 0.076586 2.596130 0.0603
R2 0.705600 Mean-dependent var. − 0.025000
Adjusted R2 0.632000 S.D.-dependent var. 0.102127
S.E. of regression 0.061954 Akaike info. criterion − 2.463664
Sum squared resid 0.015353 Schwarz criterion − 2.533077
Log likelihood 9.390991 Hannan-Quinn criterion − 2.741531
F-statistic 9.586968 Durbin-Watson stat. 1.268122
Prob. (F-statistic) 0.036352
Table 4 Building the model with deposits as the only factor
Dependent variable: GDPMethod: Least squaresDate: August 17, 2018; Time: 09:50Sample: 2012–2017Included observations: 8
Variable Coefficient Std. error t-statistic Prob.
Deposits 0.001444 7.94E−05 18.18842 0.0000
C 1.842422 0.195590 9.419830 0.0001
R2 0.982186 Mean-dependent var. 5.342500
Adjusted R2 0.979217 S.D.-dependent var. 0.686497
S.E. of regression 0.098967 Akaike info. criterion − 1.575745
Sum squared resid 0.058767 Schwarz criterion − 1.555885
Log likelihood 8.302981 Hannan-Quinn criterion − 1.709695
F-statistic 330.8186 Durbin-Watson stat. 1.996863
Prob. (F-statistic) 0.000002
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Equation involving deposits, remittances, and loans as factors
Meanwhile, if we add the credit factor, the new model will appear as GDP = 1.769447
+ 0.001193 (deposits) + 8.10 (remittances) + 0.000342 (loans). What is noticeable is
that R2 is still high at 98.5% even in this model, when all factors are considered
together. Even remittances have a high coefficient, and this makes sense because a
growth in deposits as a consequence of the large amounts of liquidity in the hands of
citizens (due to remittances) brings positive effects to the economy. Statistically, this
conclusion is valid as the value of Prob. (F-statistics) = 0.0004 while F-statistics =
86.77472. For the demonstration of the relationship in Kosovo, please refer to Table 8.
DiscussionThe goal of any country is to achieve a high level of economic growth, as this would
lead to better living standards, better prosperity, and a more comfortable life for its
Table 5 Building the model with deposits and loans as the factors
Dependent variable: GDPMethod: Least squaresDate: August 17, 2018; Time: 09:52Sample: 2012–2017Included observations: 8
Variable Coefficient Std. error t-statistic Prob.
Deposits 0.001121 0.000387 2.896729 0.0339
Credits 0.000459 0.000538 0.853755 0.4322
C 1.771827 0.216571 8.181280 0.0004
R2 0.984453 Mean-dependent var. 5.342500
Adjusted R2 0.978234 S.D.-dependent var. 0.686497
S.E. of regression 0.101281 Akaike info. criterion − 1.461830
Sum squared resid 0.051290 Schwarz criterion − 1.432040
Log likelihood 8.847321 Hannan-Quinn criterion − 1.662756
F-statistic 158.2999 Durbin-Watson stat. 1.675376
Prob. (F-statistic) 0.000030
Table 6 Building the model with remittances as the only factor
Dependent variable: GDPMethod: Least squaresDate: August 17, 2018; Time: 10:04Sample: 2012–2017Included observations: 8
Variable Coefficient Std. error t-statistic Prob.
Remittances 0.001043 0.001269 0.821843 0.4326
C 4.764384 0.746056 6.386096 0.0007
R2 0.101181 Mean-dependent var. 5.342500
Adjusted R2 − 0.048622 S.D.-dependent var. 0.686497
S.E. of regression 0.702989 Akaike info. criterion 2.345366
Sum squared resid 2.965159 Schwarz criterion 2.365226
Log likelihood − 7.381464 Hannan-Quinn criterion 2.211416
F-statistic 0.675427 Durbin-Watson stat. 0.427663
Prob. (F-statistic) 0.442591
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people (Sinha & Sinha, 1998). In addition, governments in every country aim “to
reduce poverty and increase the level of national income” (Rasmidatta, 2011).
Therefore, achieving economic growth requires governments to adopt different types of
policies such as promoting savings, stimulating investment, and increasing internal
production (Rasmidatta, 2011); also, for developing countries in the SEE region such as
Kosovo, the government needs to collaborate with Central Bank for investing in the
financial education of youth which is “the future product of efforts that are made
today” (Ribaj, Meçe, Cinaj, & Kadrimi, 2020). Undoubtedly, investment contributes to
aggregate growth; however, investment cannot be raised without increasing the amount
of savings. In order for a country to achieve sustainable economic development, it
needs to increase its aggregate savings, which will in turn contribute to greater
Table 7 Building the model with deposits and remittances as factors
Dependent variable: GDPMethod: Least squaresDate: August 17, 2018; Time: 09:55Sample: 2012–2017Included observations: 8
Variable Coefficient Std. error t-statistic Prob.
Deposits 0.001426 8.60E−05 16.57972 0.0000
Remittances 0.000143 0.000194 0.739663 0.4927
C 1.806295 0.209199 8.634341 0.0003
R2 0.983943 Mean-dependent var. 5.342500
Adjusted R2 0.977520 S.D.-dependent var. 0.686497
S.E. of regression 0.102928 Akaike info. criterion − 1.429583
Sum squared resid 0.052971 Schwarz criterion − 1.399792
Log likelihood 8.718331 Hannan-Quinn criterion − 1.630508
F-statistic 153.1972 Durbin-Watson stat. 1.399778
Prob. (F-statistic) 0.000033
Table 8 Building the model with deposits, remittances, and loans as factors
Dependent variable: GDPMethod: Least squaresDate: August 17, 2018; Time: 09:58Sample: 2012–2017Included observations: 8
Variable Coefficient Std. error t-statistic Prob.
Deposits 0.001193 0.000480 2.487145 0.0677
Remittances 8.10E−05 0.000245 0.330938 0.7573
Credits 0.000342 0.000691 0.494168 0.6471
C 1.769447 0.238993 7.403744 0.0018
R2 0.984867 Mean-dependent var. 5.342500
Adjusted R2 0.973517 S.D.-dependent var. 0.686497
S.E. of regression 0.111717 Akaike info. criterion − 1.238842
Sum squared resid 0.049923 Schwarz criterion − 1.199121
Log likelihood 8.955369 Hannan-Quinn criterion − 1.506743
F-statistic 86.77472 Durbin-Watson stat. 1.412433
Prob. (F-statistic) 0.000427
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 8 of 13
investments and higher GDP growth. This also means that more savings, specifically in
developing countries, “leads to less consumption, which could also result in a larger
amount of capital investment and finally a higher rate of economic growth”
(Rasmidatta, 2011). In that regard, Kosovo should aim to provide an open climate for
encouraging the accumulation of savings because they bring a higher level of financial
capital. As previously mentioned, financial capital is an important contributor to GDP
growth as it increases opportunities for investing in production and innovation in a
country by providing an additional income stream for society.
One way for governments to achieve economic growth, reduce poverty, and increase
national incomes is to apply policies such as increasing savings to encourage an
increase in investment in the domestic financial capital. Knowing that investment is
one of the major factors influencing economic growth, one of the main ways to
increase it is by expanding the size of savings/deposits in the commercial banks of
developing countries.
Several studies have observed the relationship between savings and economic growth.
Solow (1956) stressed the importance of saving on economic growth in 1956, when
arguing that larger savings result in higher investments and increased production.
McKinnon (1973) and Shaw (1973) reinforced the idea that savings are important in a
country’s economic development because they contribute to increased investment
which accelerates economic growth. To explore the causal relationship between savings
and economic growth, Sajid and Sarfraz (2008) used the correctional correction
technique and correction vector and concluded that there is a long-term inter-
relationship between saving and GDP. Other scholars argue that the development of
consumption habits creates a positive correlation between saving and GDP growth to-
wards sustainable economic development in developing countries (Carroll, Overland, &
Weil, 2000). Furthermore, Anoruo and Ahmad (2001) conducted a study which “uti-
lized co-integration and vector error correction model (VECM) to explore the causal
relationship between economic growth and growth rate of domestic savings,” and their
results determined the existence of a “long-run relationship between economic growth
and growth rate of savings” (Anoruo & Ahmad, 2001, p. 1).
Thirlwall studied the role of financial liberalization in order to stimulate savings and
investments, and as a result Egypt’s economic growth. According to Thirlwall (2002)
“the challenge of increasing savings is very important for Egypt in order to maintain
the growth rate and increase the investment rate,” while Romm (2003) analyzed the
degree of interaction between private savings, investment, and growth through
Johansen VECM and concluded that the growth of domestic savings/deposits has both
a direct and indirect impact on the economic growth of a country.
Economic growth has a positive effect on domestic savings. Alguacil, Cuadros, and
Orts (2004) sustain this conclusion in support of Solow’s model which deliberates that
higher savings lead to higher economic growth. Other studies express the opposite.
Interestingly, Lean and Song (2008) conducted a study analyzing the relationship
between China’s domestic savings and economic growth, noting that economic growth
in China was co-integrated with two other variables: saving households and increased
savings by enterprises/businesses. In the short term, there is a cause-and-effect relation-
ship between China’s household economy and China’s growth, while in the long run,
there is an unjustifiable shortage of economic growth that leads to increased savings
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 9 of 13
from enterprises/businesses. Another analysis of the cause-and-effect relationship be-
tween economy and savings for emerging economies was conducted by Misztal, who
argued that there is a causal relationship between domestic savings/deposits and GDP
growth (Misztal, 2011).
Developing countries, differently from developed countries have a much more
important relationship between increasing domestic savings and economic growth of
the country. Businesses in developed countries have varying financial resources
available at low cost; they also have a major investment in infrastructure, technology,
and development and do not necessarily need to attract foreign investors. This
correlation does not occur in developed countries. In order to understand the causal
relationship between savings and economic growth in Nigeria as a developing country,
Olapido used the Toda, Yamamoto, Dolado, and Lutkepohl (TYDL) methodologies
(Olapido, 2010). In this study, the variables of savings and economic growth were
integrated into a long-term equilibrium relationship. The same methodology will be ap-
plied to discover this relationship in the case of Kosovo as well.
The autoregressive distribute lag (ARDL) method was applied by Budha (2014) to
study the relationship between domestic savings, investment, and growth of Nepal, a
developing country. Budha used the annual data reports for 1974–2010 for the study.
At the end of the study, empirical results showed the existence of co-integration be-
tween domestic savings, investment, and gross domestic product. Each of these indica-
tors was tested in a multiple regression analysis, as a dependent variable. Between the
domestic savings and GDP, there is a two-way causality in the short run. The same re-
sult was achieved for investments and GDP. According to a study conducted by Sabra
and Eltalla (2016), on the effects of domestic investment on economic growth, they
concluded that the effects are significantly positive—that is, increases in domestic in-
vestments have contributed to the country’s economic growth.
Another study comes from Hundie (2014), on the causal link between saving,
investment, and economic growth, and it was based on annual data from periods
1969–1970 and 2010–2011. According to Hundie’s survey results, there is co-
integration between gross domestic savings, gross domestic investment, and Gross Do-
mestic Product as dependent variables. Both the short- and long-term investments
showed a significant positive impact on economic growth. “The current savings of
Kosovars have served as the main potential of financial resources for capital investment
in Kosovo” and have made an indisputable and irreplaceable contribution to the devel-
opment and growth of the economy of Kosovo (Mexhuani & Ribaj, 2018, p. 139). In-
creasing the accumulation of domestic savings would offer multiple benefits to
Kosovo’s economy.
Kosovo needs to mobilize internal savings to achieve the desired economic
development. For this strategy to be implemented, it would require well-organized,
competitive, and flexible financial institutions. Ribaj and Ilollari (2019) argued, in their
article for Albania as part of Southeastern European (SEE) countries, that competition
in the banking system is at a relatively low level and that no best practice is being ap-
plied by any other bank in SEE countries either. The Central Bank of Kosovo (CBK)
and Kosovo’s commercial banks have a major role to play in winning the trust of Koso-
vars and enhance the accumulation of domestic savings for the purpose of financial
capital formation and then allowing that capital to be invested appropriately and freely
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 10 of 13
in ventures that bring economic development to Kosovo. According to Cinaj, Meçe,
Ribaj, and Kadrimi (2020), in developing countries, central bank and commercial banks
continuously need to adjust policy implementation, legal and regulatory framework
which govern banking activities. Lending is the main mechanism through which savings
are transformed into investment in Kosovo. However, lending in developing countries
is limited. Lack of lending to businesses in the Southeastern European developing
countries (with Kosovo being a part of) creates a significant limitation for the develop-
ment in these countries. The biggest limitations occur to businesses5 that invest in
modern production lines, machineries, and technology that are important for reducing
production costs, increasing productivity, and improving competitiveness. Based on the
data and report-analyses of the Central Bank of Kosovo, we have identified these lend-
ing limitations in Kosovo. In addition, interviews with bank executives point out to two
reasons for the slowdown in deposits growth and the discrepancy between the short-
term nature of deposits in Kosovo and the medium- and long-term necessity of funds
by industries (as mentioned in the reports of the Central Bank of Kosovo in 2016 and
2017).
According to Agu (1984) “foreign capital cannot create permanent basis for higher
standard of living in [the] future,” on the contrary, “greater dependence on domestic
sources facilitates a more successful implementation of any planned economic
development.” Since the end of the 2008 global crisis, aid trends for developing
countries are declining and do not match current needs—countries need an ever-
growing volume of financial resources with the lowest cost to boost their economic de-
velopment, but this has become difficult to secure, even from depositors. According to
Ribaj, Ilollari, and Scalera (2019) even after 10 years from the last financial crisis, people
are still afraid to deposit all of their savings in banks and deposit withdrawals are con-
sidered to be the most “commonplace” activity. Dependence on foreign funds poses
further disadvantages because it creates an economic dependence of the borrowing
country from the lenders which might increase the foreign currency exchange risks (as
exp. crisis case of Greece, Argentina, etc.).
Investment resources in most of the developing countries (as Kosovo) come largely
from abroad, especially foreign direct investment and debt. However, the high
dependence of developing countries on external sources limits their independency and
these countries might face coercive policies for misusing their resources. Their
economic downturn is further aggravated by debts. Similarly, many developing
countries have a large deficit in current and commercial accounts, funded by foreign
grants and loans. Even a small change in external capital flows can cause internal
economic downturn. The accumulation of domestic savings will help reduce the
vulnerability arising from dependence on foreign financing and provide a sustainable
long-term financing base for investments in developing countries.
A rise in aggregate savings would yield larger investments associated with higher
GDP growth. As a result, the high rates of savings increase the amount of capital and
lead to higher economic growth in the country. Also, based on the theory of marginal
inclination to save, revenue growth leads to the expansion of the savings rate. When
5According to Bisat, El-Erian, and Helbling in 1997 in a detailed analysis of growth, investment, and savingsfor Arab economies, it was noted that private sector investment was considered the engine of economicgrowth.
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 11 of 13
talking about the relationship between savings and economic growth, it cannot be
denied that an increase in aggregate savings would boost investment and promote
economic growth. This is more evident in developing countries where the largest
source of financial capital stems from savings deposited in commercial banks. Past
experiences have shown that low saving rates have led to deficits in the budget and
balance of the country’s account.
ConclusionsThe root test confirms stationarity and the hypothesis H0 is disproved because the
Granger causality test confirms a causal relationship between Kosovo’s deposits (X) and
economic growth (Y). Regression results showed that deposits have a significant
positive impact on Kosovo’s economic growth. This research concluded that the
increase in the accumulation of savings from commercial banks in Kosovo has a
positive effect on Kosovo’s economic growth, as well as that remittances and loans are
also an important enabling factor in driving the economy of Kosovo through a direct
impact on investment.
Therefore, increasing the level of accumulation of domestic savings in the Kosovo
banking system will help reduce unemployment, enable greater technological
development, and increase Kosovo’s GDP and people’s well-being. This strategy will re-
duce the risks to the country’s economy, as a major problem faced by some developing
countries is typically the burden of external debts and dependence on international
banks. Hence, the state of Kosovo should initiate strategies to promote the accumula-
tion of domestic savings to accelerate sustainable economic growth in the country.
For further studies, we recommend a study on whether there should be some limit
indicators set out in the CBK regulatory framework for limiting the large gap that
exists between the interest rate on loans and the interest rate on deposits in Kosovo, or
the establishment of some requirements for ensuring transparency in the construction
of the interest rate on loans.
AbbreviationsADF: Augmented Dickey-Fuller; ARDL: Autoregressive distribute lag; CBK: Central Bank of Kosovo; DF: Dickey-Fuller;GC: Ganger causality; GDP: Gross domestic product; SEE: Southeastern European; VECM: Vector error correction model
AcknowledgementsThe authors acknowledge Kosovo’s Central Bank and Commercial Banks for their support in providing data andinformation asked by them.
Authors’ contributionsArtur Ribaj designed coordinated this research and drafted the manuscript. Fitim Mexhuani collected the data andcarried out the data analyses. The authors read and approved the final article.
FundingThis article did not have donation or other funding sources.
Availability of data and materialsThe datasets analyzed during the current study are available in the Central Bank of Kosovo repository, https://bqk-kos.org/?lang=en. All data generated during this study are included in this published article.
Competing interestsThe authors declare that they have no competing interests.
Author details1Faculty of Economics, University of Tirana, Tirana, Albania. 2Europian University of Tirana, Tirana, Albania.
Ribaj and Mexhuani Journal of Innovation and Entrepreneurship (2021) 10:1 Page 12 of 13
Received: 2 May 2020 Accepted: 17 November 2020
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